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gtDesign: Convex Optimal Designs for Group Testing Experiments

Finite candidate-set approximate optimal designs for group testing and related experiments, using convex optimization and equivalence checks. Implements the information matrix and cost structure for the prevalence / sensitivity / specificity model used in Huang and colleagues (2020), as in Chi-Kuang Yeh, Weng Kee Wong, and Julie Zhou (<doi:10.48550/arXiv.2508.08445>).

Version: 0.1.0
Imports: CVXR (≥ 1.8.1), tibble, MASS
Suggests: testthat (≥ 3.0.0), dplyr, knitr
Published: 2026-04-09
DOI: 10.32614/CRAN.package.gtDesign
Author: Chi-Kuang Yeh ORCID iD [aut, cre], Julie Zhou [aut], Weng Kee Wong [ctb]
Maintainer: Chi-Kuang Yeh <cyeh at gsu.edu>
BugReports: https://github.com/chikuang/gtDesign/issues
License: GPL-3
URL: https://github.com/chikuang/gtDesign, https://arxiv.org/abs/2508.08445
NeedsCompilation: no
Materials: README
CRAN checks: gtDesign results

Documentation:

Reference manual: gtDesign.html , gtDesign.pdf

Downloads:

Package source: gtDesign_0.1.0.tar.gz
Windows binaries: r-devel: gtDesign_0.1.0.zip, r-release: gtDesign_0.1.0.zip, r-oldrel: gtDesign_0.1.0.zip
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): gtDesign_0.1.0.tgz, r-oldrel (x86_64): gtDesign_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.